Community Detection as an Inference Problem

Abstract

We express community detection as an inference problem of determining the most likely arrangement of communities. We then apply belief propagation and mean-field theory to this problem, and show that this leads to fast, accurate algorithms for community detection.

4 pages, 2 figures

References in corpus (3)

• Comparing community structure identification
• Statistical Mechanics of Community Detection
• Subnetwork hierarchies of biochemical pathways

Cited by in corpus (12)

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• Near linear time algorithm to detect community structures in large-scale networks
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• Robustness of community structure in networks
• A Bayesian Approach to Network Modularity
• Structural Inference of Hierarchies in Networks
• Detection of node group membership in networks with group overlap
• Community Detection in Complex Networks by Dynamical Simplex Evolution
• Community Structure in Large Networks: Natural Cluster Sizes and the Absence of Large Well-Defined Clusters
• Detecting modules in dense weighted networks with the Potts method
• Retrieving information from a noisy "knowledge network"